HR Dataset

Dataset statistics

Number of variables	36
Number of observations	311
Missing cells	215
Missing cells (%)	1.9%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	402.5 KiB
Average record size in memory	1.3 KiB

Variable types

Categorical	25
Numeric	10
Boolean	1

Alerts

`Employee_Name` has a high cardinality: 311 distinct values	High cardinality
`DOB` has a high cardinality: 307 distinct values	High cardinality
`DateofHire` has a high cardinality: 101 distinct values	High cardinality
`DateofTermination` has a high cardinality: 96 distinct values	High cardinality
`LastPerformanceReview_Date` has a high cardinality: 137 distinct values	High cardinality
`EmpID` is highly overall correlated with `PerfScoreID` and 4 other fields	High correlation
`DeptID` is highly overall correlated with `Salary` and 8 other fields	High correlation
`Salary` is highly overall correlated with `DeptID` and 5 other fields	High correlation
`PositionID` is highly overall correlated with `DeptID` and 7 other fields	High correlation
`Zip` is highly overall correlated with `DeptID` and 5 other fields	High correlation
`ManagerID` is highly overall correlated with `DeptID` and 5 other fields	High correlation
`EngagementSurvey` is highly overall correlated with `EmpID` and 5 other fields	High correlation
`SpecialProjectsCount` is highly overall correlated with `DeptID` and 7 other fields	High correlation
`DaysLateLast30` is highly overall correlated with `EmpID` and 5 other fields	High correlation
`MarriedID` is highly overall correlated with `MaritalStatusID` and 2 other fields	High correlation
`MaritalStatusID` is highly overall correlated with `MarriedID` and 1 other fields	High correlation
`GenderID` is highly overall correlated with `Sex`	High correlation
`EmpStatusID` is highly overall correlated with `Termd` and 2 other fields	High correlation
`PerfScoreID` is highly overall correlated with `EmpID` and 4 other fields	High correlation
`FromDiversityJobFairID` is highly overall correlated with `RaceDesc` and 1 other fields	High correlation
`Termd` is highly overall correlated with `EmpStatusID` and 2 other fields	High correlation
`Position` is highly overall correlated with `DeptID` and 10 other fields	High correlation
`State` is highly overall correlated with `DeptID` and 9 other fields	High correlation
`Sex` is highly overall correlated with `GenderID`	High correlation
`MaritalDesc` is highly overall correlated with `MarriedID` and 1 other fields	High correlation
`HispanicLatino` is highly overall correlated with `Position` and 5 other fields	High correlation
`RaceDesc` is highly overall correlated with `FromDiversityJobFairID` and 3 other fields	High correlation
`DateofTermination` is highly overall correlated with `MarriedID` and 8 other fields	High correlation
`TermReason` is highly overall correlated with `EmpStatusID` and 4 other fields	High correlation
`EmploymentStatus` is highly overall correlated with `EmpStatusID` and 2 other fields	High correlation
`Department` is highly overall correlated with `DeptID` and 9 other fields	High correlation
`ManagerName` is highly overall correlated with `DeptID` and 10 other fields	High correlation
`RecruitmentSource` is highly overall correlated with `FromDiversityJobFairID` and 3 other fields	High correlation
`PerformanceScore` is highly overall correlated with `EmpID` and 3 other fields	High correlation
`EmpSatisfaction` is highly overall correlated with `EmpID` and 3 other fields	High correlation
`Absences` is highly overall correlated with `DateofTermination`	High correlation
`DateofTermination` has 207 (66.6%) missing values	Missing
`ManagerID` has 8 (2.6%) missing values	Missing
`Employee_Name` is uniformly distributed	Uniform
`EmpID` is uniformly distributed	Uniform
`DOB` is uniformly distributed	Uniform
`DateofTermination` is uniformly distributed	Uniform
`Employee_Name` has unique values	Unique
`EmpID` has unique values	Unique
`SpecialProjectsCount` has 241 (77.5%) zeros	Zeros
`DaysLateLast30` has 278 (89.4%) zeros	Zeros

Reproduction

Analysis started	2022-12-17 23:45:29.657325
Analysis finished	2022-12-17 23:46:07.508932
Duration	37.85 seconds
Software version	pandas-profiling vv3.5.0
Download configuration	config.json

Employee_Name
Categorical

HIGH CARDINALITY
UNIFORM
UNIQUE

Distinct	311
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	21.9 KiB

Adinolfi, Wilson K	1
O'hare, Lynn	1
Patronick, Lucas	1
Panjwani, Nina	1
Ozark, Travis	1
Other values (306)	306

Length

Max length	25
Median length	22
Mean length	14.755627
Min length	8

Characters and Unicode

Total characters	4589
Distinct characters	55
Distinct categories	5 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	311 ?
Unique (%)	100.0%

Sample

1st row	Adinolfi, Wilson K
2nd row	Ait Sidi, Karthikeyan
3rd row	Akinkuolie, Sarah
4th row	Alagbe,Trina
5th row	Anderson, Carol

Common Values

Value	Count	Frequency (%)
Adinolfi, Wilson K	1	0.3%
O'hare, Lynn	1	0.3%
Patronick, Lucas	1	0.3%
Panjwani, Nina	1	0.3%
Ozark, Travis	1	0.3%
Owad, Clinton	1	0.3%
Osturnka, Adeel	1	0.3%
Onque, Jasmine	1	0.3%
Oliver, Brooke	1	0.3%
Nowlan, Kristie	1	0.3%
Other values (301)	301	96.8%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
smith	5	0.8%
susan	4	0.6%
michael	4	0.6%
linda	3	0.5%
robinson	3	0.5%
j	3	0.5%
amy	3	0.5%
jennifer	3	0.5%
lisa	3	0.5%
barbara	3	0.5%
Other values (556)	601	94.6%

Most occurring characters

Value	Count	Frequency (%)
	448	9.8%
a	405	8.8%
e	376	8.2%
n	347	7.6%
,	311	6.8%
i	285	6.2%
r	256	5.6%
o	234	5.1%
l	206	4.5%
s	144	3.1%
Other values (45)	1577	34.4%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	3175	69.2%
Uppercase Letter	649	14.1%
Space Separator	448	9.8%
Other Punctuation	314	6.8%
Dash Punctuation	3	0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	405	12.8%
e	376	11.8%
n	347	10.9%
i	285	9.0%
r	256	8.1%
o	234	7.4%
l	206	6.5%
s	144	4.5%
t	141	4.4%
h	111	3.5%
Other values (16)	670	21.1%

Uppercase Letter

Value	Count	Frequency (%)
S	59	9.1%
M	53	8.2%
B	52	8.0%
J	50	7.7%
C	48	7.4%
L	45	6.9%
A	37	5.7%
R	34	5.2%
D	33	5.1%
K	30	4.6%
Other values (15)	208	32.0%

Other Punctuation

Value	Count	Frequency (%)
,	311	99.0%
'	3	1.0%

Space Separator

Value	Count	Frequency (%)
	448	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	3	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	3824	83.3%
Common	765	16.7%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	405	10.6%
e	376	9.8%
n	347	9.1%
i	285	7.5%
r	256	6.7%
o	234	6.1%
l	206	5.4%
s	144	3.8%
t	141	3.7%
h	111	2.9%
Other values (41)	1319	34.5%

Common

Value	Count	Frequency (%)
	448	58.6%
,	311	40.7%
'	3	0.4%
-	3	0.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4589	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	448	9.8%
a	405	8.8%
e	376	8.2%
n	347	7.6%
,	311	6.8%
i	285	6.2%
r	256	5.6%
o	234	5.1%
l	206	4.5%
s	144	3.1%
Other values (45)	1577	34.4%

EmpID
Real number (ℝ)

HIGH CORRELATION
UNIFORM
UNIQUE

Distinct	311
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	10156

Minimum	10001
Maximum	10311
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.6 KiB

Quantile statistics

Minimum	10001
5-th percentile	10016.5
Q1	10078.5
median	10156
Q3	10233.5
95-th percentile	10295.5
Maximum	10311
Range	310
Interquartile range (IQR)	155

Descriptive statistics

Standard deviation	89.922189
Coefficient of variation (CV)	0.008854095
Kurtosis	-1.2
Mean	10156
Median Absolute Deviation (MAD)	78
Skewness	0
Sum	3158516
Variance	8086
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
10026	1	0.3%
10303	1	0.3%
10005	1	0.3%
10148	1	0.3%
10041	1	0.3%
10281	1	0.3%
10021	1	0.3%
10121	1	0.3%
10078	1	0.3%
10104	1	0.3%
Other values (301)	301	96.8%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
10001	1	0.3%
10002	1	0.3%
10003	1	0.3%
10004	1	0.3%
10005	1	0.3%
10006	1	0.3%
10007	1	0.3%
10008	1	0.3%
10009	1	0.3%
10010	1	0.3%

Value	Count	Frequency (%)
10311	1	0.3%
10310	1	0.3%
10309	1	0.3%
10308	1	0.3%
10307	1	0.3%
10306	1	0.3%
10305	1	0.3%
10304	1	0.3%
10303	1	0.3%
10302	1	0.3%

MarriedID
Categorical

Distinct	2
Distinct (%)	0.6%
Missing	0
Missing (%)	0.0%
Memory size	17.7 KiB

0	187
1	124

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	311
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	1
3rd row	1
4th row	1
5th row	0

Common Values

Value	Count	Frequency (%)
0	187	60.1%
1	124	39.9%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
0	187	60.1%
1	124	39.9%

Most occurring characters

Value	Count	Frequency (%)
0	187	60.1%
1	124	39.9%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	311	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	187	60.1%
1	124	39.9%

Most occurring scripts

Value	Count	Frequency (%)
Common	311	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	187	60.1%
1	124	39.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	311	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	187	60.1%
1	124	39.9%

MaritalStatusID
Categorical

Distinct	5
Distinct (%)	1.6%
Missing	0
Missing (%)	0.0%
Memory size	17.7 KiB

0	137
1	124
2	30
3	12
4	8

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	311
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	1
3rd row	1
4th row	1
5th row	2

Common Values

Value	Count	Frequency (%)
0	137	44.1%
1	124	39.9%
2	30	9.6%
3	12	3.9%
4	8	2.6%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
0	137	44.1%
1	124	39.9%
2	30	9.6%
3	12	3.9%
4	8	2.6%

Most occurring characters

Value	Count	Frequency (%)
0	137	44.1%
1	124	39.9%
2	30	9.6%
3	12	3.9%
4	8	2.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	311	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	137	44.1%
1	124	39.9%
2	30	9.6%
3	12	3.9%
4	8	2.6%

Most occurring scripts

Value	Count	Frequency (%)
Common	311	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	137	44.1%
1	124	39.9%
2	30	9.6%
3	12	3.9%
4	8	2.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	311	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	137	44.1%
1	124	39.9%
2	30	9.6%
3	12	3.9%
4	8	2.6%

GenderID
Categorical

Distinct	2
Distinct (%)	0.6%
Missing	0
Missing (%)	0.0%
Memory size	17.7 KiB

0	176
1	135

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	311
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	176	56.6%
1	135	43.4%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
0	176	56.6%
1	135	43.4%

Most occurring characters

Value	Count	Frequency (%)
0	176	56.6%
1	135	43.4%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	311	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	176	56.6%
1	135	43.4%

Most occurring scripts

Value	Count	Frequency (%)
Common	311	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	176	56.6%
1	135	43.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	311	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	176	56.6%
1	135	43.4%

EmpStatusID
Categorical

Distinct	5
Distinct (%)	1.6%
Missing	0
Missing (%)	0.0%
Memory size	17.7 KiB

1	184
5	88
3	14
4	14
2	11

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	311
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	5
3rd row	5
4th row	1
5th row	5

Common Values

Value	Count	Frequency (%)
1	184	59.2%
5	88	28.3%
3	14	4.5%
4	14	4.5%
2	11	3.5%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
1	184	59.2%
5	88	28.3%
3	14	4.5%
4	14	4.5%
2	11	3.5%

Most occurring characters

Value	Count	Frequency (%)
1	184	59.2%
5	88	28.3%
3	14	4.5%
4	14	4.5%
2	11	3.5%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	311	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	184	59.2%
5	88	28.3%
3	14	4.5%
4	14	4.5%
2	11	3.5%

Most occurring scripts

Value	Count	Frequency (%)
Common	311	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	184	59.2%
5	88	28.3%
3	14	4.5%
4	14	4.5%
2	11	3.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	311	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	184	59.2%
5	88	28.3%
3	14	4.5%
4	14	4.5%
2	11	3.5%

DeptID
Real number (ℝ)

Distinct	6
Distinct (%)	1.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	4.6109325

Minimum	1
Maximum	6
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.6 KiB

Quantile statistics

Minimum	1
5-th percentile	3
Q1	5
median	5
Q3	5
95-th percentile	6
Maximum	6
Range	5
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	1.0834872
Coefficient of variation (CV)	0.23498224
Kurtosis	2.2414339
Mean	4.6109325
Median Absolute Deviation (MAD)	0
Skewness	-1.5363915
Sum	1434
Variance	1.1739446
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
5	208	66.9%
3	50	16.1%
6	32	10.3%
4	10	3.2%
1	10	3.2%
2	1	0.3%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	10	3.2%
2	1	0.3%
3	50	16.1%
4	10	3.2%
5	208	66.9%
6	32	10.3%

Value	Count	Frequency (%)
6	32	10.3%
5	208	66.9%
4	10	3.2%
3	50	16.1%
2	1	0.3%
1	10	3.2%

PerfScoreID
Categorical

Distinct	4
Distinct (%)	1.3%
Missing	0
Missing (%)	0.0%
Memory size	17.7 KiB

3	243
4	37
2	18
1	13

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	311
Distinct characters	4
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	4
2nd row	3
3rd row	3
4th row	3
5th row	3

Common Values

Value	Count	Frequency (%)
3	243	78.1%
4	37	11.9%
2	18	5.8%
1	13	4.2%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
3	243	78.1%
4	37	11.9%
2	18	5.8%
1	13	4.2%

Most occurring characters

Value	Count	Frequency (%)
3	243	78.1%
4	37	11.9%
2	18	5.8%
1	13	4.2%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	311	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
3	243	78.1%
4	37	11.9%
2	18	5.8%
1	13	4.2%

Most occurring scripts

Value	Count	Frequency (%)
Common	311	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
3	243	78.1%
4	37	11.9%
2	18	5.8%
1	13	4.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	311	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
3	243	78.1%
4	37	11.9%
2	18	5.8%
1	13	4.2%

FromDiversityJobFairID
Categorical

Distinct	2
Distinct (%)	0.6%
Missing	0
Missing (%)	0.0%
Memory size	17.7 KiB

0	282
1	29

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	311
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	282	90.7%
1	29	9.3%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
0	282	90.7%
1	29	9.3%

Most occurring characters

Value	Count	Frequency (%)
0	282	90.7%
1	29	9.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	311	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	282	90.7%
1	29	9.3%

Most occurring scripts

Value	Count	Frequency (%)
Common	311	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	282	90.7%
1	29	9.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	311	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	282	90.7%
1	29	9.3%

Salary
Real number (ℝ)

Distinct	308
Distinct (%)	99.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	69020.685

Minimum	45046
Maximum	250000
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.6 KiB

Quantile statistics

Minimum	45046
5-th percentile	46999.5
Q1	55501.5
median	62810
Q3	72036
95-th percentile	108106.5
Maximum	250000
Range	204954
Interquartile range (IQR)	16534.5

Descriptive statistics

Standard deviation	25156.637
Coefficient of variation (CV)	0.36447968
Kurtosis	15.452149
Mean	69020.685
Median Absolute Deviation (MAD)	7982
Skewness	3.3061808
Sum	21465433
Variance	6.3285638 × 10⁸
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
63025	2	0.6%
57815	2	0.6%
61242	2	0.6%
66738	1	0.3%
68829	1	0.3%
53060	1	0.3%
47414	1	0.3%
63051	1	0.3%
71966	1	0.3%
52674	1	0.3%
Other values (298)	298	95.8%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
45046	1	0.3%
45069	1	0.3%
45115	1	0.3%
45395	1	0.3%
45433	1	0.3%
45998	1	0.3%
46120	1	0.3%
46335	1	0.3%
46428	1	0.3%
46430	1	0.3%

Value	Count	Frequency (%)
250000	1	0.3%
220450	1	0.3%
180000	1	0.3%
178000	1	0.3%
170500	1	0.3%
157000	1	0.3%
150290	1	0.3%
148999	1	0.3%
140920	1	0.3%
138888	1	0.3%

Termd
Categorical

Distinct	2
Distinct (%)	0.6%
Missing	0
Missing (%)	0.0%
Memory size	17.7 KiB

0	207
1	104

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	311
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	1
3rd row	1
4th row	0
5th row	1

Common Values

Value	Count	Frequency (%)
0	207	66.6%
1	104	33.4%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
0	207	66.6%
1	104	33.4%

Most occurring characters

Value	Count	Frequency (%)
0	207	66.6%
1	104	33.4%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	311	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	207	66.6%
1	104	33.4%

Most occurring scripts

Value	Count	Frequency (%)
Common	311	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	207	66.6%
1	104	33.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	311	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	207	66.6%
1	104	33.4%

PositionID
Real number (ℝ)

Distinct	30
Distinct (%)	9.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	16.845659

Minimum	1
Maximum	30
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.6 KiB

Quantile statistics

Minimum	1
5-th percentile	3
Q1	18
median	19
Q3	20
95-th percentile	24
Maximum	30
Range	29
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	6.2234187
Coefficient of variation (CV)	0.36943753
Kurtosis	0.81234602
Mean	16.845659
Median Absolute Deviation (MAD)	1
Skewness	-1.2316765
Sum	5239
Variance	38.730941
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=30)

Value	Count	Frequency (%)
19	137	44.1%
20	57	18.3%
3	27	8.7%
18	13	4.2%
24	9	2.9%
14	8	2.6%
9	8	2.6%
15	5	1.6%
28	5	1.6%
8	5	1.6%
Other values (20)	37	11.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	3	1.0%
2	3	1.0%
3	27	8.7%
4	4	1.3%
5	1	0.3%
6	1	0.3%
7	1	0.3%
8	5	1.6%
9	8	2.6%
10	1	0.3%

Value	Count	Frequency (%)
30	1	0.3%
29	1	0.3%
28	5	1.6%
27	2	0.6%
26	2	0.6%
25	1	0.3%
24	9	2.9%
23	2	0.6%
22	3	1.0%
21	3	1.0%

Position
Categorical

Distinct	32
Distinct (%)	10.3%
Missing	0
Missing (%)	0.0%
Memory size	23.7 KiB

Production Technician I	137
Production Technician II	57
Area Sales Manager	27
Production Manager	14
Software Engineer	10
Other values (27)	66

Length

Max length	28
Median length	24
Mean length	20.720257
Min length	3

Characters and Unicode

Total characters	6444
Distinct characters	38
Distinct categories	5 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	14 ?
Unique (%)	4.5%

Sample

1st row	Production Technician I
2nd row	Sr. DBA
3rd row	Production Technician II
4th row	Production Technician I
5th row	Production Technician I

Common Values

Value	Count	Frequency (%)
Production Technician I	137	44.1%
Production Technician II	57	18.3%
Area Sales Manager	27	8.7%
Production Manager	14	4.5%
Software Engineer	10	3.2%
IT Support	8	2.6%
Data Analyst	7	2.3%
Sr. Network Engineer	5	1.6%
Database Administrator	5	1.6%
Network Engineer	5	1.6%
Other values (22)	36	11.6%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
production	208	24.1%
technician	194	22.5%
i	140	16.2%
ii	57	6.6%
manager	50	5.8%
sales	31	3.6%
area	27	3.1%
engineer	20	2.3%
it	13	1.5%
software	11	1.3%
Other values (29)	113	13.1%

Most occurring characters

Value	Count	Frequency (%)
n	726	11.3%
i	656	10.2%
c	618	9.6%
	554	8.6%
o	473	7.3%
a	426	6.6%
e	412	6.4%
r	387	6.0%
t	306	4.7%
I	277	4.3%
Other values (28)	1609	25.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	4931	76.5%
Uppercase Letter	945	14.7%
Space Separator	554	8.6%
Other Punctuation	10	0.2%
Dash Punctuation	4	0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
n	726	14.7%
i	656	13.3%
c	618	12.5%
o	473	9.6%
a	426	8.6%
e	412	8.4%
r	387	7.8%
t	306	6.2%
u	222	4.5%
d	218	4.4%
Other values (12)	487	9.9%

Uppercase Letter

Value	Count	Frequency (%)
I	277	29.3%
P	210	22.2%
T	207	21.9%
S	65	6.9%
A	56	5.9%
M	50	5.3%
D	30	3.2%
E	23	2.4%
B	12	1.3%
N	10	1.1%
Other values (2)	5	0.5%

Other Punctuation

Value	Count	Frequency (%)
.	9	90.0%
&	1	10.0%

Space Separator

Value	Count	Frequency (%)
	554	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	4	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	5876	91.2%
Common	568	8.8%

Most frequent character per script

Latin

Value	Count	Frequency (%)
n	726	12.4%
i	656	11.2%
c	618	10.5%
o	473	8.0%
a	426	7.2%
e	412	7.0%
r	387	6.6%
t	306	5.2%
I	277	4.7%
u	222	3.8%
Other values (24)	1373	23.4%

Common

Value	Count	Frequency (%)
	554	97.5%
.	9	1.6%
-	4	0.7%
&	1	0.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	6444	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
n	726	11.3%
i	656	10.2%
c	618	9.6%
	554	8.6%
o	473	7.3%
a	426	6.6%
e	412	6.4%
r	387	6.0%
t	306	4.7%
I	277	4.3%
Other values (28)	1609	25.0%

State
Categorical

Distinct	28
Distinct (%)	9.0%
Missing	0
Missing (%)	0.0%
Memory size	18.0 KiB

MA	276
CT	6
TX	3
VT	2
UT	1
Other values (23)	23

Length

Max length	2
Median length	2
Mean length	2
Min length	2

Characters and Unicode

Total characters	622
Distinct characters	22
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	24 ?
Unique (%)	7.7%

Sample

1st row	MA
2nd row	MA
3rd row	MA
4th row	MA
5th row	MA

Common Values

Value	Count	Frequency (%)
MA	276	88.7%
CT	6	1.9%
TX	3	1.0%
VT	2	0.6%
UT	1	0.3%
AZ	1	0.3%
ND	1	0.3%
OR	1	0.3%
MT	1	0.3%
NV	1	0.3%
Other values (18)	18	5.8%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
ma	276	88.7%
ct	6	1.9%
tx	3	1.0%
vt	2	0.6%
ny	1	0.3%
va	1	0.3%
al	1	0.3%
wa	1	0.3%
ca	1	0.3%
oh	1	0.3%
Other values (18)	18	5.8%

Most occurring characters

Value	Count	Frequency (%)
A	283	45.5%
M	278	44.7%
T	14	2.3%
C	9	1.4%
N	7	1.1%
V	4	0.6%
I	3	0.5%
X	3	0.5%
O	3	0.5%
H	2	0.3%
Other values (12)	16	2.6%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	622	100.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
A	283	45.5%
M	278	44.7%
T	14	2.3%
C	9	1.4%
N	7	1.1%
V	4	0.6%
I	3	0.5%
X	3	0.5%
O	3	0.5%
H	2	0.3%
Other values (12)	16	2.6%

Most occurring scripts

Value	Count	Frequency (%)
Latin	622	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
A	283	45.5%
M	278	44.7%
T	14	2.3%
C	9	1.4%
N	7	1.1%
V	4	0.6%
I	3	0.5%
X	3	0.5%
O	3	0.5%
H	2	0.3%
Other values (12)	16	2.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	622	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
A	283	45.5%
M	278	44.7%
T	14	2.3%
C	9	1.4%
N	7	1.1%
V	4	0.6%
I	3	0.5%
X	3	0.5%
O	3	0.5%
H	2	0.3%
Other values (12)	16	2.6%

Zip
Real number (ℝ)

Distinct	158
Distinct (%)	50.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	6555.4823

Minimum	1013
Maximum	98052
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.6 KiB

Quantile statistics

Minimum	1013
5-th percentile	1725.5
Q1	1901.5
median	2132
Q3	2355
95-th percentile	38674.5
Maximum	98052
Range	97039
Interquartile range (IQR)	453.5

Descriptive statistics

Standard deviation	16908.397
Coefficient of variation (CV)	2.5792758
Kurtosis	16.187425
Mean	6555.4823
Median Absolute Deviation (MAD)	230
Skewness	4.1054943
Sum	2038755
Variance	2.8589389 × 10⁸
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1886	13	4.2%
1810	7	2.3%
2045	7	2.3%
2176	7	2.3%
2451	7	2.3%
2169	6	1.9%
2110	6	1.9%
2170	5	1.6%
2324	5	1.6%
1460	5	1.6%
Other values (148)	243	78.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1013	1	0.3%
1040	1	0.3%
1420	2	0.6%
1450	2	0.6%
1460	5	1.6%
1545	1	0.3%
1550	1	0.3%
1701	2	0.6%
1721	1	0.3%
1730	2	0.6%

Value	Count	Frequency (%)
98052	1	0.3%
97756	1	0.3%
90007	1	0.3%
89139	1	0.3%
85006	1	0.3%
84111	1	0.3%
83706	1	0.3%
80820	1	0.3%
78789	1	0.3%
78230	1	0.3%

DOB
Categorical

HIGH CARDINALITY
UNIFORM

Distinct	307
Distinct (%)	98.7%
Missing	0
Missing (%)	0.0%
Memory size	19.9 KiB

09/09/65	2
06/14/87	2
09/22/76	2
07/07/84	2
05/12/80	1
Other values (302)	302

Length

Max length	8
Median length	8
Mean length	8
Min length	8

Characters and Unicode

Total characters	2488
Distinct characters	11
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	303 ?
Unique (%)	97.4%

Sample

1st row	07/10/83
2nd row	05/05/75
3rd row	09/19/88
4th row	09/27/88
5th row	09/08/89

Common Values

Value	Count	Frequency (%)
09/09/65	2	0.6%
06/14/87	2	0.6%
09/22/76	2	0.6%
07/07/84	2	0.6%
05/12/80	1	0.3%
11/06/84	1	0.3%
05/01/79	1	0.3%
05/19/82	1	0.3%
11/24/79	1	0.3%
12/11/76	1	0.3%
Other values (297)	297	95.5%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
09/09/65	2	0.6%
09/22/76	2	0.6%
07/07/84	2	0.6%
06/14/87	2	0.6%
01/12/74	1	0.3%
09/27/88	1	0.3%
09/08/89	1	0.3%
05/22/77	1	0.3%
05/24/79	1	0.3%
02/18/83	1	0.3%
Other values (297)	297	95.5%

Most occurring characters

Value	Count	Frequency (%)
/	622	25.0%
0	426	17.1%
1	278	11.2%
8	249	10.0%
7	198	8.0%
2	180	7.2%
5	119	4.8%
9	116	4.7%
6	115	4.6%
4	95	3.8%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	1866	75.0%
Other Punctuation	622	25.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	426	22.8%
1	278	14.9%
8	249	13.3%
7	198	10.6%
2	180	9.6%
5	119	6.4%
9	116	6.2%
6	115	6.2%
4	95	5.1%
3	90	4.8%

Other Punctuation

Value	Count	Frequency (%)
/	622	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	2488	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
/	622	25.0%
0	426	17.1%
1	278	11.2%
8	249	10.0%
7	198	8.0%
2	180	7.2%
5	119	4.8%
9	116	4.7%
6	115	4.6%
4	95	3.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	2488	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
/	622	25.0%
0	426	17.1%
1	278	11.2%
8	249	10.0%
7	198	8.0%
2	180	7.2%
5	119	4.8%
9	116	4.7%
6	115	4.6%
4	95	3.8%

Sex
Categorical

Distinct	2
Distinct (%)	0.6%
Missing	0
Missing (%)	0.0%
Memory size	17.9 KiB

F	176
M	135

Length

Max length	2
Median length	1
Mean length	1.4340836
Min length	1

Characters and Unicode

Total characters	446
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	M
2nd row	M
3rd row	F
4th row	F
5th row	F

Common Values

Value	Count	Frequency (%)
F	176	56.6%
M	135	43.4%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
f	176	56.6%
m	135	43.4%

Most occurring characters

Value	Count	Frequency (%)
F	176	39.5%
M	135	30.3%
	135	30.3%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	311	69.7%
Space Separator	135	30.3%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
F	176	56.6%
M	135	43.4%

Space Separator

Value	Count	Frequency (%)
	135	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	311	69.7%
Common	135	30.3%

Most frequent character per script

Latin

Value	Count	Frequency (%)
F	176	56.6%
M	135	43.4%

Common

Value	Count	Frequency (%)
	135	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	446	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
F	176	39.5%
M	135	30.3%
	135	30.3%

MaritalDesc
Categorical

Distinct	5
Distinct (%)	1.6%
Missing	0
Missing (%)	0.0%
Memory size	19.5 KiB

Single	137
Married	124
Divorced	30
Separated	12
Widowed	8

Length

Max length	9
Median length	8
Mean length	6.733119
Min length	6

Characters and Unicode

Total characters	2094
Distinct characters	18
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Single
2nd row	Married
3rd row	Married
4th row	Married
5th row	Divorced

Common Values

Value	Count	Frequency (%)
Single	137	44.1%
Married	124	39.9%
Divorced	30	9.6%
Separated	12	3.9%
Widowed	8	2.6%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
single	137	44.1%
married	124	39.9%
divorced	30	9.6%
separated	12	3.9%
widowed	8	2.6%

Most occurring characters

Value	Count	Frequency (%)
e	323	15.4%
i	299	14.3%
r	290	13.8%
d	182	8.7%
S	149	7.1%
a	148	7.1%
l	137	6.5%
g	137	6.5%
n	137	6.5%
M	124	5.9%
Other values (8)	168	8.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	1783	85.1%
Uppercase Letter	311	14.9%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	323	18.1%
i	299	16.8%
r	290	16.3%
d	182	10.2%
a	148	8.3%
l	137	7.7%
g	137	7.7%
n	137	7.7%
o	38	2.1%
v	30	1.7%
Other values (4)	62	3.5%

Uppercase Letter

Value	Count	Frequency (%)
S	149	47.9%
M	124	39.9%
D	30	9.6%
W	8	2.6%

Most occurring scripts

Value	Count	Frequency (%)
Latin	2094	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	323	15.4%
i	299	14.3%
r	290	13.8%
d	182	8.7%
S	149	7.1%
a	148	7.1%
l	137	6.5%
g	137	6.5%
n	137	6.5%
M	124	5.9%
Other values (8)	168	8.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	2094	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	323	15.4%
i	299	14.3%
r	290	13.8%
d	182	8.7%
S	149	7.1%
a	148	7.1%
l	137	6.5%
g	137	6.5%
n	137	6.5%
M	124	5.9%
Other values (8)	168	8.0%

CitizenDesc
Categorical

Distinct	3
Distinct (%)	1.0%
Missing	0
Missing (%)	0.0%
Memory size	20.6 KiB

US Citizen	295
Eligible NonCitizen	12
Non-Citizen	4

Length

Max length	19
Median length	10
Mean length	10.360129
Min length	10

Characters and Unicode

Total characters	3222
Distinct characters	16
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	US Citizen
2nd row	US Citizen
3rd row	US Citizen
4th row	US Citizen
5th row	US Citizen

Common Values

Value	Count	Frequency (%)
US Citizen	295	94.9%
Eligible NonCitizen	12	3.9%
Non-Citizen	4	1.3%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
us	295	47.7%
citizen	295	47.7%
eligible	12	1.9%
noncitizen	12	1.9%
non-citizen	4	0.6%

Most occurring characters

Value	Count	Frequency (%)
i	646	20.0%
n	327	10.1%
e	323	10.0%
C	311	9.7%
t	311	9.7%
z	311	9.7%
	307	9.5%
U	295	9.2%
S	295	9.2%
l	24	0.7%
Other values (6)	72	2.2%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	1982	61.5%
Uppercase Letter	929	28.8%
Space Separator	307	9.5%
Dash Punctuation	4	0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
i	646	32.6%
n	327	16.5%
e	323	16.3%
t	311	15.7%
z	311	15.7%
l	24	1.2%
o	16	0.8%
g	12	0.6%
b	12	0.6%

Uppercase Letter

Value	Count	Frequency (%)
C	311	33.5%
U	295	31.8%
S	295	31.8%
N	16	1.7%
E	12	1.3%

Space Separator

Value	Count	Frequency (%)
	307	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	4	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	2911	90.3%
Common	311	9.7%

Most frequent character per script

Latin

Value	Count	Frequency (%)
i	646	22.2%
n	327	11.2%
e	323	11.1%
C	311	10.7%
t	311	10.7%
z	311	10.7%
U	295	10.1%
S	295	10.1%
l	24	0.8%
N	16	0.5%
Other values (4)	52	1.8%

Common

Value	Count	Frequency (%)
	307	98.7%
-	4	1.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	3222	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
i	646	20.0%
n	327	10.1%
e	323	10.0%
C	311	9.7%
t	311	9.7%
z	311	9.7%
	307	9.5%
U	295	9.2%
S	295	9.2%
l	24	0.7%
Other values (6)	72	2.2%

HispanicLatino
Boolean

Distinct	2
Distinct (%)	0.6%
Missing	0
Missing (%)	0.0%
Memory size	439.0 B

False	283
True	28

Common Values (Table)
Common Values (Plot)

Value	Count	Frequency (%)
False	283	91.0%
True	28	9.0%

RaceDesc
Categorical

Distinct	6
Distinct (%)	1.9%
Missing	0
Missing (%)	0.0%
Memory size	20.7 KiB

White	187
Black or African American	80
Asian	29
Two or more races	11
American Indian or Alaska Native	3

Length

Max length	32
Median length	5
Mean length	10.839228
Min length	5

Characters and Unicode

Total characters	3371
Distinct characters	26
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	0.3%

Sample

1st row	White
2nd row	White
3rd row	White
4th row	White
5th row	White

Common Values

Value	Count	Frequency (%)
White	187	60.1%
Black or African American	80	25.7%
Asian	29	9.3%
Two or more races	11	3.5%
American Indian or Alaska Native	3	1.0%
Hispanic	1	0.3%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
white	187	31.4%
or	94	15.8%
american	83	13.9%
black	80	13.4%
african	80	13.4%
asian	29	4.9%
two	11	1.8%
more	11	1.8%
races	11	1.8%
indian	3	0.5%
Other values (3)	7	1.2%

Most occurring characters

Value	Count	Frequency (%)
i	387	11.5%
a	296	8.8%
e	295	8.8%
	285	8.5%
r	279	8.3%
c	255	7.6%
n	199	5.9%
A	195	5.8%
t	190	5.6%
h	187	5.5%
Other values (16)	803	23.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	2606	77.3%
Uppercase Letter	480	14.2%
Space Separator	285	8.5%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
i	387	14.9%
a	296	11.4%
e	295	11.3%
r	279	10.7%
c	255	9.8%
n	199	7.6%
t	190	7.3%
h	187	7.2%
o	116	4.5%
m	94	3.6%
Other values (8)	308	11.8%

Uppercase Letter

Value	Count	Frequency (%)
A	195	40.6%
W	187	39.0%
B	80	16.7%
T	11	2.3%
I	3	0.6%
N	3	0.6%
H	1	0.2%

Space Separator

Value	Count	Frequency (%)
	285	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	3086	91.5%
Common	285	8.5%

Most frequent character per script

Latin

Value	Count	Frequency (%)
i	387	12.5%
a	296	9.6%
e	295	9.6%
r	279	9.0%
c	255	8.3%
n	199	6.4%
A	195	6.3%
t	190	6.2%
h	187	6.1%
W	187	6.1%
Other values (15)	616	20.0%

Common

Value	Count	Frequency (%)
	285	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	3371	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
i	387	11.5%
a	296	8.8%
e	295	8.8%
	285	8.5%
r	279	8.3%
c	255	7.6%
n	199	5.9%
A	195	5.8%
t	190	5.6%
h	187	5.5%
Other values (16)	803	23.8%

DateofHire
Categorical

Distinct	101
Distinct (%)	32.5%
Missing	0
Missing (%)	0.0%
Memory size	20.1 KiB

1/10/2011	14
3/30/2015	12
1/5/2015	11
9/29/2014	11
7/5/2011	10
Other values (96)	253

Length

Max length	10
Median length	9
Mean length	8.7009646
Min length	8

Characters and Unicode

Total characters	2706
Distinct characters	11
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	54 ?
Unique (%)	17.4%

Sample

1st row	7/5/2011
2nd row	3/30/2015
3rd row	7/5/2011
4th row	1/7/2008
5th row	7/11/2011

Common Values

Value	Count	Frequency (%)
1/10/2011	14	4.5%
3/30/2015	12	3.9%
1/5/2015	11	3.5%
9/29/2014	11	3.5%
7/5/2011	10	3.2%
5/16/2011	10	3.2%
9/30/2013	9	2.9%
4/2/2012	9	2.9%
9/26/2011	9	2.9%
7/7/2014	9	2.9%
Other values (91)	207	66.6%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
1/10/2011	14	4.5%
3/30/2015	12	3.9%
1/5/2015	11	3.5%
9/29/2014	11	3.5%
7/5/2011	10	3.2%
5/16/2011	10	3.2%
9/26/2011	9	2.9%
7/7/2014	9	2.9%
7/8/2013	9	2.9%
4/2/2012	9	2.9%
Other values (91)	207	66.6%

Most occurring characters

Value	Count	Frequency (%)
1	630	23.3%
/	622	23.0%
2	463	17.1%
0	400	14.8%
5	115	4.2%
4	102	3.8%
3	101	3.7%
7	89	3.3%
9	74	2.7%
6	66	2.4%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	2084	77.0%
Other Punctuation	622	23.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	630	30.2%
2	463	22.2%
0	400	19.2%
5	115	5.5%
4	102	4.9%
3	101	4.8%
7	89	4.3%
9	74	3.6%
6	66	3.2%
8	44	2.1%

Other Punctuation

Value	Count	Frequency (%)
/	622	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	2706	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	630	23.3%
/	622	23.0%
2	463	17.1%
0	400	14.8%
5	115	4.2%
4	102	3.8%
3	101	3.7%
7	89	3.3%
9	74	2.7%
6	66	2.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	2706	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	630	23.3%
/	622	23.0%
2	463	17.1%
0	400	14.8%
5	115	4.2%
4	102	3.8%
3	101	3.7%
7	89	3.3%
9	74	2.7%
6	66	2.4%

DateofTermination
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING
UNIFORM

Distinct	96
Distinct (%)	92.3%
Missing	207
Missing (%)	66.6%
Memory size	13.3 KiB

9/7/2015	2
5/17/2016	2
11/4/2015	2
6/18/2013	2
4/1/2013	2
Other values (91)	94

Length

Max length	10
Median length	9
Mean length	8.7788462
Min length	8

Characters and Unicode

Total characters	913
Distinct characters	11
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	88 ?
Unique (%)	84.6%

Sample

1st row	6/16/2016
2nd row	9/24/2012
3rd row	9/6/2016
4th row	1/12/2017
5th row	9/19/2016

Common Values

Value	Count	Frequency (%)
9/7/2015	2	0.6%
5/17/2016	2	0.6%
11/4/2015	2	0.6%
6/18/2013	2	0.6%
4/1/2013	2	0.6%
4/4/2014	2	0.6%
8/19/2018	2	0.6%
9/24/2012	2	0.6%
1/12/2014	1	0.3%
8/19/2013	1	0.3%
Other values (86)	86	27.7%
(Missing)	207	66.6%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
9/7/2015	2	1.9%
11/4/2015	2	1.9%
6/18/2013	2	1.9%
4/1/2013	2	1.9%
4/4/2014	2	1.9%
8/19/2018	2	1.9%
9/24/2012	2	1.9%
5/17/2016	2	1.9%
8/4/2017	1	1.0%
8/7/2014	1	1.0%
Other values (86)	86	82.7%

Most occurring characters

Value	Count	Frequency (%)
/	208	22.8%
1	187	20.5%
2	157	17.2%
0	114	12.5%
5	54	5.9%
6	43	4.7%
4	42	4.6%
8	32	3.5%
9	31	3.4%
3	24	2.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	705	77.2%
Other Punctuation	208	22.8%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	187	26.5%
2	157	22.3%
0	114	16.2%
5	54	7.7%
6	43	6.1%
4	42	6.0%
8	32	4.5%
9	31	4.4%
3	24	3.4%
7	21	3.0%

Other Punctuation

Value	Count	Frequency (%)
/	208	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	913	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
/	208	22.8%
1	187	20.5%
2	157	17.2%
0	114	12.5%
5	54	5.9%
6	43	4.7%
4	42	4.6%
8	32	3.5%
9	31	3.4%
3	24	2.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	913	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
/	208	22.8%
1	187	20.5%
2	157	17.2%
0	114	12.5%
5	54	5.9%
6	43	4.7%
4	42	4.6%
8	32	3.5%
9	31	3.4%
3	24	2.6%

TermReason
Categorical

Distinct	18
Distinct (%)	5.8%
Missing	0
Missing (%)	0.0%
Memory size	22.2 KiB

N/A-StillEmployed	207
Another position	20
unhappy	14
more money	11
career change	9
Other values (13)	50

Length

Max length	32
Median length	17
Mean length	15.546624
Min length	5

Characters and Unicode

Total characters	4835
Distinct characters	30
Distinct categories	5 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	3 ?
Unique (%)	1.0%

Sample

1st row	N/A-StillEmployed
2nd row	career change
3rd row	hours
4th row	N/A-StillEmployed
5th row	return to school

Common Values

Value	Count	Frequency (%)
N/A-StillEmployed	207	66.6%
Another position	20	6.4%
unhappy	14	4.5%
more money	11	3.5%
career change	9	2.9%
hours	8	2.6%
attendance	7	2.3%
return to school	5	1.6%
relocation out of area	5	1.6%
no-call, no-show	4	1.3%
Other values (8)	21	6.8%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
n/a-stillemployed	207	51.1%
position	20	4.9%
another	20	4.9%
unhappy	14	3.5%
more	11	2.7%
money	11	2.7%
career	9	2.2%
change	9	2.2%
return	8	2.0%
hours	8	2.0%
Other values (29)	88	21.7%

Most occurring characters

Value	Count	Frequency (%)
l	650	13.4%
o	354	7.3%
e	339	7.0%
t	309	6.4%
i	283	5.9%
p	259	5.4%
m	244	5.0%
y	239	4.9%
A	227	4.7%
d	225	4.7%
Other values (20)	1706	35.3%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	3462	71.6%
Uppercase Letter	850	17.6%
Dash Punctuation	218	4.5%
Other Punctuation	211	4.4%
Space Separator	94	1.9%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
l	650	18.8%
o	354	10.2%
e	339	9.8%
t	309	8.9%
i	283	8.2%
p	259	7.5%
m	244	7.0%
y	239	6.9%
d	225	6.5%
n	127	3.7%
Other values (10)	433	12.5%

Uppercase Letter

Value	Count	Frequency (%)
A	227	26.7%
N	207	24.4%
S	207	24.4%
E	207	24.4%
L	1	0.1%
F	1	0.1%

Other Punctuation

Value	Count	Frequency (%)
/	207	98.1%
,	4	1.9%

Dash Punctuation

Value	Count	Frequency (%)
-	218	100.0%

Space Separator

Value	Count	Frequency (%)
	94	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	4312	89.2%
Common	523	10.8%

Most frequent character per script

Latin

Value	Count	Frequency (%)
l	650	15.1%
o	354	8.2%
e	339	7.9%
t	309	7.2%
i	283	6.6%
p	259	6.0%
m	244	5.7%
y	239	5.5%
A	227	5.3%
d	225	5.2%
Other values (16)	1183	27.4%

Common

Value	Count	Frequency (%)
-	218	41.7%
/	207	39.6%
	94	18.0%
,	4	0.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4835	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
l	650	13.4%
o	354	7.3%
e	339	7.0%
t	309	6.4%
i	283	5.9%
p	259	5.4%
m	244	5.0%
y	239	4.9%
A	227	4.7%
d	225	4.7%
Other values (20)	1706	35.3%

EmploymentStatus
Categorical

Distinct	3
Distinct (%)	1.0%
Missing	0
Missing (%)	0.0%
Memory size	20.9 KiB

Active	207
Voluntarily Terminated	88
Terminated for Cause	16

Length

Max length	22
Median length	6
Mean length	11.247588
Min length	6

Characters and Unicode

Total characters	3498
Distinct characters	21
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Active
2nd row	Voluntarily Terminated
3rd row	Voluntarily Terminated
4th row	Active
5th row	Voluntarily Terminated

Common Values

Value	Count	Frequency (%)
Active	207	66.6%
Voluntarily Terminated	88	28.3%
Terminated for Cause	16	5.1%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
active	207	48.0%
terminated	104	24.1%
voluntarily	88	20.4%
for	16	3.7%
cause	16	3.7%

Most occurring characters

Value	Count	Frequency (%)
e	431	12.3%
t	399	11.4%
i	399	11.4%
r	208	5.9%
a	208	5.9%
A	207	5.9%
c	207	5.9%
v	207	5.9%
n	192	5.5%
l	176	5.0%
Other values (11)	864	24.7%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	2963	84.7%
Uppercase Letter	415	11.9%
Space Separator	120	3.4%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	431	14.5%
t	399	13.5%
i	399	13.5%
r	208	7.0%
a	208	7.0%
c	207	7.0%
v	207	7.0%
n	192	6.5%
l	176	5.9%
u	104	3.5%
Other values (6)	432	14.6%

Uppercase Letter

Value	Count	Frequency (%)
A	207	49.9%
T	104	25.1%
V	88	21.2%
C	16	3.9%

Space Separator

Value	Count	Frequency (%)
	120	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	3378	96.6%
Common	120	3.4%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	431	12.8%
t	399	11.8%
i	399	11.8%
r	208	6.2%
a	208	6.2%
A	207	6.1%
c	207	6.1%
v	207	6.1%
n	192	5.7%
l	176	5.2%
Other values (10)	744	22.0%

Common

Value	Count	Frequency (%)
	120	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	3498	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	431	12.3%
t	399	11.4%
i	399	11.4%
r	208	5.9%
a	208	5.9%
A	207	5.9%
c	207	5.9%
v	207	5.9%
n	192	5.5%
l	176	5.0%
Other values (11)	864	24.7%

Department
Categorical

Distinct	6
Distinct (%)	1.9%
Missing	0
Missing (%)	0.0%
Memory size	21.6 KiB

Production	209
IT/IS	50
Sales	31
Software Engineering	11
Admin Offices	9

Length

Max length	20
Median length	17
Mean length	13.861736
Min length	5

Characters and Unicode

Total characters	4311
Distinct characters	27
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	0.3%

Sample

1st row	Production
2nd row	IT/IS
3rd row	Production
4th row	Production
5th row	Production

Common Values

Value	Count	Frequency (%)
Production	209	67.2%
IT/IS	50	16.1%
Sales	31	10.0%
Software Engineering	11	3.5%
Admin Offices	9	2.9%
Executive Office	1	0.3%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
production	209	63.0%
it/is	50	15.1%
sales	31	9.3%
software	11	3.3%
engineering	11	3.3%
admin	9	2.7%
offices	9	2.7%
executive	1	0.3%
office	1	0.3%

Most occurring characters

Value	Count	Frequency (%)
	1484	34.4%
o	429	10.0%
i	251	5.8%
n	251	5.8%
r	231	5.4%
t	221	5.1%
c	220	5.1%
d	218	5.1%
u	210	4.9%
P	209	4.8%
Other values (17)	587	13.6%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	2295	53.2%
Space Separator	1484	34.4%
Uppercase Letter	482	11.2%
Other Punctuation	50	1.2%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
o	429	18.7%
i	251	10.9%
n	251	10.9%
r	231	10.1%
t	221	9.6%
c	220	9.6%
d	218	9.5%
u	210	9.2%
e	76	3.3%
a	42	1.8%
Other values (8)	146	6.4%

Uppercase Letter

Value	Count	Frequency (%)
P	209	43.4%
I	100	20.7%
S	92	19.1%
T	50	10.4%
E	12	2.5%
O	10	2.1%
A	9	1.9%

Space Separator

Value	Count	Frequency (%)
	1484	100.0%

Other Punctuation

Value	Count	Frequency (%)
/	50	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	2777	64.4%
Common	1534	35.6%

Most frequent character per script

Latin

Value	Count	Frequency (%)
o	429	15.4%
i	251	9.0%
n	251	9.0%
r	231	8.3%
t	221	8.0%
c	220	7.9%
d	218	7.9%
u	210	7.6%
P	209	7.5%
I	100	3.6%
Other values (15)	437	15.7%

Common

Value	Count	Frequency (%)
	1484	96.7%
/	50	3.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4311	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	1484	34.4%
o	429	10.0%
i	251	5.8%
n	251	5.8%
r	231	5.4%
t	221	5.1%
c	220	5.1%
d	218	5.1%
u	210	4.9%
P	209	4.8%
Other values (17)	587	13.6%

ManagerName
Categorical

Distinct	21
Distinct (%)	6.8%
Missing	0
Missing (%)	0.0%
Memory size	21.3 KiB

Michael Albert	22
Kissy Sullivan	22
Elijiah Gray	22
Kelley Spirea	22
Brannon Miller	22
Other values (16)	201

Length

Max length	18
Median length	16
Mean length	12.665595
Min length	8

Characters and Unicode

Total characters	3939
Distinct characters	41
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Michael Albert
2nd row	Simon Roup
3rd row	Kissy Sullivan
4th row	Elijiah Gray
5th row	Webster Butler

Common Values

Value	Count	Frequency (%)
Michael Albert	22	7.1%
Kissy Sullivan	22	7.1%
Elijiah Gray	22	7.1%
Kelley Spirea	22	7.1%
Brannon Miller	22	7.1%
Ketsia Liebig	21	6.8%
David Stanley	21	6.8%
Amy Dunn	21	6.8%
Webster Butler	21	6.8%
Janet King	19	6.1%
Other values (11)	98	31.5%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
michael	22	3.5%
kissy	22	3.5%
sullivan	22	3.5%
elijiah	22	3.5%
gray	22	3.5%
kelley	22	3.5%
spirea	22	3.5%
brannon	22	3.5%
miller	22	3.5%
albert	22	3.5%
Other values (34)	411	65.1%

Most occurring characters

Value	Count	Frequency (%)
e	402	10.2%
n	327	8.3%
	320	8.1%
i	320	8.1%
a	313	7.9%
l	280	7.1%
r	231	5.9%
t	186	4.7%
o	125	3.2%
y	121	3.1%
Other values (31)	1314	33.4%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	2976	75.6%
Uppercase Letter	636	16.1%
Space Separator	320	8.1%
Other Punctuation	7	0.2%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	402	13.5%
n	327	11.0%
i	320	10.8%
a	313	10.5%
l	280	9.4%
r	231	7.8%
t	186	6.2%
o	125	4.2%
y	121	4.1%
u	101	3.4%
Other values (13)	570	19.2%

Uppercase Letter

Value	Count	Frequency (%)
S	105	16.5%
K	84	13.2%
B	67	10.5%
D	64	10.1%
M	58	9.1%
A	52	8.2%
L	41	6.4%
J	40	6.3%
E	26	4.1%
R	24	3.8%
Other values (6)	75	11.8%

Space Separator

Value	Count	Frequency (%)
	320	100.0%

Other Punctuation

Value	Count	Frequency (%)
.	7	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	3612	91.7%
Common	327	8.3%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	402	11.1%
n	327	9.1%
i	320	8.9%
a	313	8.7%
l	280	7.8%
r	231	6.4%
t	186	5.1%
o	125	3.5%
y	121	3.3%
S	105	2.9%
Other values (29)	1202	33.3%

Common

Value	Count	Frequency (%)
	320	97.9%
.	7	2.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	3939	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	402	10.2%
n	327	8.3%
	320	8.1%
i	320	8.1%
a	313	7.9%
l	280	7.1%
r	231	5.9%
t	186	4.7%
o	125	3.2%
y	121	3.1%
Other values (31)	1314	33.4%

ManagerID
Real number (ℝ)

HIGH CORRELATION
MISSING

Distinct	23
Distinct (%)	7.6%
Missing	8
Missing (%)	2.6%
Infinite	0
Infinite (%)	0.0%
Mean	14.570957

Minimum	1
Maximum	39
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.6 KiB

Quantile statistics

Minimum	1
5-th percentile	2
Q1	10
median	15
Q3	19
95-th percentile	22
Maximum	39
Range	38
Interquartile range (IQR)	9

Descriptive statistics

Standard deviation	8.0783056
Coefficient of variation (CV)	0.55441146
Kurtosis	1.6084223
Mean	14.570957
Median Absolute Deviation (MAD)	4
Skewness	0.75927123
Sum	4415
Variance	65.259021
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=23)

Value	Count	Frequency (%)
20	22	7.1%
16	22	7.1%
12	22	7.1%
18	22	7.1%
22	21	6.8%
11	21	6.8%
19	21	6.8%
14	21	6.8%
2	19	6.1%
4	17	5.5%
Other values (13)	95	30.5%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	6	1.9%
2	19	6.1%
3	1	0.3%
4	17	5.5%
5	7	2.3%
6	4	1.3%
7	14	4.5%
9	2	0.6%
10	9	2.9%
11	21	6.8%

Value	Count	Frequency (%)
39	13	4.2%
30	1	0.3%
22	21	6.8%
21	13	4.2%
20	22	7.1%
19	21	6.8%
18	22	7.1%
17	14	4.5%
16	22	7.1%
15	3	1.0%

RecruitmentSource
Categorical

Distinct	9
Distinct (%)	2.9%
Missing	0
Missing (%)	0.0%
Memory size	20.6 KiB

Indeed	87
LinkedIn	76
Google Search	49
Employee Referral	31
Diversity Job Fair	29
Other values (4)	39

Length

Max length	23
Median length	18
Mean length	10.414791
Min length	5

Characters and Unicode

Total characters	3239
Distinct characters	36
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	0.3%

Sample

1st row	LinkedIn
2nd row	Indeed
3rd row	LinkedIn
4th row	Indeed
5th row	Google Search

Common Values

Value	Count	Frequency (%)
Indeed	87	28.0%
LinkedIn	76	24.4%
Google Search	49	15.8%
Employee Referral	31	10.0%
Diversity Job Fair	29	9.3%
CareerBuilder	23	7.4%
Website	13	4.2%
Other	2	0.6%
On-line Web application	1	0.3%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
indeed	87	19.3%
linkedin	76	16.9%
google	49	10.9%
search	49	10.9%
employee	31	6.9%
referral	31	6.9%
diversity	29	6.4%
job	29	6.4%
fair	29	6.4%
careerbuilder	23	5.1%
Other values (5)	18	4.0%

Most occurring characters

Value	Count	Frequency (%)
e	600	18.5%
d	273	8.4%
n	242	7.5%
r	240	7.4%
i	202	6.2%
I	163	5.0%
o	159	4.9%
	140	4.3%
l	136	4.2%
a	134	4.1%
Other values (26)	950	29.3%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	2549	78.7%
Uppercase Letter	549	16.9%
Space Separator	140	4.3%
Dash Punctuation	1	< 0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	600	23.5%
d	273	10.7%
n	242	9.5%
r	240	9.4%
i	202	7.9%
o	159	6.2%
l	136	5.3%
a	134	5.3%
k	76	3.0%
y	60	2.4%
Other values (11)	427	16.8%

Uppercase Letter

Value	Count	Frequency (%)
I	163	29.7%
L	76	13.8%
G	49	8.9%
S	49	8.9%
R	31	5.6%
E	31	5.6%
D	29	5.3%
J	29	5.3%
F	29	5.3%
C	23	4.2%
Other values (3)	40	7.3%

Space Separator

Value	Count	Frequency (%)
	140	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	3098	95.6%
Common	141	4.4%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	600	19.4%
d	273	8.8%
n	242	7.8%
r	240	7.7%
i	202	6.5%
I	163	5.3%
o	159	5.1%
l	136	4.4%
a	134	4.3%
k	76	2.5%
Other values (24)	873	28.2%

Common

Value	Count	Frequency (%)
	140	99.3%
-	1	0.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	3239	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	600	18.5%
d	273	8.4%
n	242	7.5%
r	240	7.4%
i	202	6.2%
I	163	5.0%
o	159	4.9%
	140	4.3%
l	136	4.2%
a	134	4.1%
Other values (26)	950	29.3%

PerformanceScore
Categorical

Distinct	4
Distinct (%)	1.3%
Missing	0
Missing (%)	0.0%
Memory size	20.6 KiB

Fully Meets	243
Exceeds	37
Needs Improvement	18
PIP	13

Length

Max length	17
Median length	11
Mean length	10.536977
Min length	3

Characters and Unicode

Total characters	3277
Distinct characters	22
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Exceeds
2nd row	Fully Meets
3rd row	Fully Meets
4th row	Fully Meets
5th row	Fully Meets

Common Values

Value	Count	Frequency (%)
Fully Meets	243	78.1%
Exceeds	37	11.9%
Needs Improvement	18	5.8%
PIP	13	4.2%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
fully	243	42.5%
meets	243	42.5%
exceeds	37	6.5%
needs	18	3.1%
improvement	18	3.1%
pip	13	2.3%

Most occurring characters

Value	Count	Frequency (%)
e	632	19.3%
l	486	14.8%
s	298	9.1%
	261	8.0%
t	261	8.0%
F	243	7.4%
u	243	7.4%
y	243	7.4%
M	243	7.4%
d	55	1.7%
Other values (12)	312	9.5%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	2418	73.8%
Uppercase Letter	598	18.2%
Space Separator	261	8.0%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	632	26.1%
l	486	20.1%
s	298	12.3%
t	261	10.8%
u	243	10.0%
y	243	10.0%
d	55	2.3%
c	37	1.5%
x	37	1.5%
m	36	1.5%
Other values (5)	90	3.7%

Uppercase Letter

Value	Count	Frequency (%)
F	243	40.6%
M	243	40.6%
E	37	6.2%
I	31	5.2%
P	26	4.3%
N	18	3.0%

Space Separator

Value	Count	Frequency (%)
	261	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	3016	92.0%
Common	261	8.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	632	21.0%
l	486	16.1%
s	298	9.9%
t	261	8.7%
F	243	8.1%
u	243	8.1%
y	243	8.1%
M	243	8.1%
d	55	1.8%
c	37	1.2%
Other values (11)	275	9.1%

Common

Value	Count	Frequency (%)
	261	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	3277	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	632	19.3%
l	486	14.8%
s	298	9.1%
	261	8.0%
t	261	8.0%
F	243	7.4%
u	243	7.4%
y	243	7.4%
M	243	7.4%
d	55	1.7%
Other values (12)	312	9.5%

EngagementSurvey
Real number (ℝ)

Distinct	119
Distinct (%)	38.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	4.11

Minimum	1.12
Maximum	5
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.6 KiB

Quantile statistics

Minimum	1.12
5-th percentile	2.4
Q1	3.69
median	4.28
Q3	4.7
95-th percentile	5
Maximum	5
Range	3.88
Interquartile range (IQR)	1.01

Descriptive statistics

Standard deviation	0.78993752
Coefficient of variation (CV)	0.19219891
Kurtosis	1.1645598
Mean	4.11
Median Absolute Deviation (MAD)	0.49
Skewness	-1.1169793
Sum	1278.21
Variance	0.62400129
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
5	56	18.0%
4.5	19	6.1%
4.3	17	5.5%
4.2	17	5.5%
4.1	16	5.1%
4.6	10	3.2%
4.7	7	2.3%
4.4	7	2.3%
3.6	7	2.3%
3.4	5	1.6%
Other values (109)	150	48.2%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1.12	1	0.3%
1.2	1	0.3%
1.56	1	0.3%
1.81	1	0.3%
1.93	1	0.3%
2	3	1.0%
2.1	1	0.3%
2.3	2	0.6%
2.33	1	0.3%
2.34	1	0.3%

Value	Count	Frequency (%)
5	56	18.0%
4.96	2	0.6%
4.94	1	0.3%
4.9	1	0.3%
4.88	1	0.3%
4.84	1	0.3%
4.83	2	0.6%
4.81	1	0.3%
4.8	3	1.0%
4.78	1	0.3%

EmpSatisfaction
Categorical

Distinct	5
Distinct (%)	1.6%
Missing	0
Missing (%)	0.0%
Memory size	17.7 KiB

3	108
5	98
4	94
2	9
1	2

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	311
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	5
2nd row	3
3rd row	3
4th row	5
5th row	4

Common Values

Value	Count	Frequency (%)
3	108	34.7%
5	98	31.5%
4	94	30.2%
2	9	2.9%
1	2	0.6%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
3	108	34.7%
5	98	31.5%
4	94	30.2%
2	9	2.9%
1	2	0.6%

Most occurring characters

Value	Count	Frequency (%)
3	108	34.7%
5	98	31.5%
4	94	30.2%
2	9	2.9%
1	2	0.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	311	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
3	108	34.7%
5	98	31.5%
4	94	30.2%
2	9	2.9%
1	2	0.6%

Most occurring scripts

Value	Count	Frequency (%)
Common	311	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
3	108	34.7%
5	98	31.5%
4	94	30.2%
2	9	2.9%
1	2	0.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	311	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
3	108	34.7%
5	98	31.5%
4	94	30.2%
2	9	2.9%
1	2	0.6%

SpecialProjectsCount
Real number (ℝ)

HIGH CORRELATION
ZEROS

Distinct	9
Distinct (%)	2.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.2186495

Minimum	0
Maximum	8
Zeros	241
Zeros (%)	77.5%
Negative	0
Negative (%)	0.0%
Memory size	2.6 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	6
Maximum	8
Range	8
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	2.3494212
Coefficient of variation (CV)	1.9278892
Kurtosis	0.64141536
Mean	1.2186495
Median Absolute Deviation (MAD)	0
Skewness	1.5392709
Sum	379
Variance	5.5197801
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=9)

Value	Count	Frequency (%)
0	241	77.5%
6	21	6.8%
5	21	6.8%
7	12	3.9%
4	9	2.9%
3	3	1.0%
8	2	0.6%
2	1	0.3%
1	1	0.3%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	241	77.5%
1	1	0.3%
2	1	0.3%
3	3	1.0%
4	9	2.9%
5	21	6.8%
6	21	6.8%
7	12	3.9%
8	2	0.6%

Value	Count	Frequency (%)
8	2	0.6%
7	12	3.9%
6	21	6.8%
5	21	6.8%
4	9	2.9%
3	3	1.0%
2	1	0.3%
1	1	0.3%
0	241	77.5%

LastPerformanceReview_Date
Categorical

Distinct	137
Distinct (%)	44.1%
Missing	0
Missing (%)	0.0%
Memory size	20.1 KiB

1/14/2019	18
2/18/2019	12
1/21/2019	10
1/28/2019	9
2/25/2019	9
Other values (132)	253

Length

Max length	10
Median length	9
Mean length	8.6848875
Min length	8

Characters and Unicode

Total characters	2701
Distinct characters	11
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	89 ?
Unique (%)	28.6%

Sample

1st row	1/17/2019
2nd row	2/24/2016
3rd row	5/15/2012
4th row	1/3/2019
5th row	2/1/2016

Common Values

Value	Count	Frequency (%)
1/14/2019	18	5.8%
2/18/2019	12	3.9%
1/21/2019	10	3.2%
1/28/2019	9	2.9%
2/25/2019	9	2.9%
1/17/2019	8	2.6%
1/7/2019	7	2.3%
1/30/2019	6	1.9%
2/11/2019	6	1.9%
2/22/2019	6	1.9%
Other values (127)	220	70.7%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
1/14/2019	18	5.8%
2/18/2019	12	3.9%
1/21/2019	10	3.2%
1/28/2019	9	2.9%
2/25/2019	9	2.9%
1/17/2019	8	2.6%
1/7/2019	7	2.3%
2/22/2019	6	1.9%
1/25/2019	6	1.9%
1/31/2019	6	1.9%
Other values (127)	220	70.7%

Most occurring characters

Value	Count	Frequency (%)
/	622	23.0%
1	615	22.8%
2	554	20.5%
0	342	12.7%
9	224	8.3%
5	76	2.8%
4	75	2.8%
3	65	2.4%
8	45	1.7%
7	43	1.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	2079	77.0%
Other Punctuation	622	23.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	615	29.6%
2	554	26.6%
0	342	16.5%
9	224	10.8%
5	76	3.7%
4	75	3.6%
3	65	3.1%
8	45	2.2%
7	43	2.1%
6	40	1.9%

Other Punctuation

Value	Count	Frequency (%)
/	622	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	2701	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
/	622	23.0%
1	615	22.8%
2	554	20.5%
0	342	12.7%
9	224	8.3%
5	76	2.8%
4	75	2.8%
3	65	2.4%
8	45	1.7%
7	43	1.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	2701	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
/	622	23.0%
1	615	22.8%
2	554	20.5%
0	342	12.7%
9	224	8.3%
5	76	2.8%
4	75	2.8%
3	65	2.4%
8	45	1.7%
7	43	1.6%

DaysLateLast30
Real number (ℝ)

HIGH CORRELATION
ZEROS

Distinct	7
Distinct (%)	2.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.414791

Minimum	0
Maximum	6
Zeros	278
Zeros (%)	89.4%
Negative	0
Negative (%)	0.0%
Memory size	2.6 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	4
Maximum	6
Range	6
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	1.2945194
Coefficient of variation (CV)	3.1208956
Kurtosis	8.8305232
Mean	0.414791
Median Absolute Deviation (MAD)	0
Skewness	3.1434676
Sum	129
Variance	1.6757805
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=7)

Value	Count	Frequency (%)
0	278	89.4%
4	8	2.6%
2	6	1.9%
5	6	1.9%
3	6	1.9%
6	6	1.9%
1	1	0.3%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	278	89.4%
1	1	0.3%
2	6	1.9%
3	6	1.9%
4	8	2.6%
5	6	1.9%
6	6	1.9%

Value	Count	Frequency (%)
6	6	1.9%
5	6	1.9%
4	8	2.6%
3	6	1.9%
2	6	1.9%
1	1	0.3%
0	278	89.4%

Absences
Real number (ℝ)

Distinct	20
Distinct (%)	6.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	10.237942

Minimum	1
Maximum	20
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.6 KiB

Quantile statistics

Minimum	1
5-th percentile	2
Q1	5
median	10
Q3	15
95-th percentile	19
Maximum	20
Range	19
Interquartile range (IQR)	10

Descriptive statistics

Standard deviation	5.8525959
Coefficient of variation (CV)	0.57165745
Kurtosis	-1.301962
Mean	10.237942
Median Absolute Deviation (MAD)	5
Skewness	0.029283457
Sum	3184
Variance	34.252878
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=20)

Value	Count	Frequency (%)
4	23	7.4%
16	23	7.4%
7	21	6.8%
2	21	6.8%
15	20	6.4%
13	17	5.5%
14	17	5.5%
3	16	5.1%
19	16	5.1%
6	16	5.1%
Other values (10)	121	38.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	14	4.5%
2	21	6.8%
3	16	5.1%
4	23	7.4%
5	12	3.9%
6	16	5.1%
7	21	6.8%
8	11	3.5%
9	14	4.5%
10	10	3.2%

Value	Count	Frequency (%)
20	14	4.5%
19	16	5.1%
18	8	2.6%
17	15	4.8%
16	23	7.4%
15	20	6.4%
14	17	5.5%
13	17	5.5%
12	8	2.6%
11	15	4.8%

Auto

The auto setting is an interpretable pairwise column metric of the following mapping:

Variable_type-Variable_type : Method, Range
Categorical-Categorical : Cramer's V, [0,1]
Numerical-Categorical : Cramer's V, [0,1] (using a discretized numerical column)
Numerical-Numerical : Spearman's ρ, [-1,1]

The number of bins used in the discretization for the Numerical-Categorical column pair can be changed using config.correlations["auto"].n_bins. The number of bins affects the granularity of the association you wish to measure.

This configuration uses the recommended metric for each pair of columns.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

First rows
Last rows

	Employee_Name	EmpID	MarriedID	MaritalStatusID	GenderID	EmpStatusID	DeptID	PerfScoreID	FromDiversityJobFairID	Salary	Termd	PositionID	Position	State	Zip	DOB	Sex	MaritalDesc	CitizenDesc	HispanicLatino	RaceDesc	DateofHire	DateofTermination	TermReason	EmploymentStatus	Department	ManagerName	ManagerID	RecruitmentSource	PerformanceScore	EngagementSurvey	EmpSatisfaction	SpecialProjectsCount	LastPerformanceReview_Date	Absences
0	Adinolfi, Wilson K	10026	0	0	1	1	5	4	0	62506	0	19	Production Technician I	MA	1960	07/10/83	M	Single	US Citizen	No	White	7/5/2011	NaN	N/A-StillEmployed	Active	Production	Michael Albert	22.0	LinkedIn	Exceeds	4.60	5	0	1/17/2019	1
1	Ait Sidi, Karthikeyan	10084	1	1	1	5	3	3	0	104437	1	27	Sr. DBA	MA	2148	05/05/75	M	Married	US Citizen	No	White	3/30/2015	6/16/2016	career change	Voluntarily Terminated	IT/IS	Simon Roup	4.0	Indeed	Fully Meets	4.96	3	6	2/24/2016	17
2	Akinkuolie, Sarah	10196	1	1	0	5	5	3	0	64955	1	20	Production Technician II	MA	1810	09/19/88	F	Married	US Citizen	No	White	7/5/2011	9/24/2012	hours	Voluntarily Terminated	Production	Kissy Sullivan	20.0	LinkedIn	Fully Meets	3.02	3	0	5/15/2012	3
3	Alagbe,Trina	10088	1	1	0	1	5	3	0	64991	0	19	Production Technician I	MA	1886	09/27/88	F	Married	US Citizen	No	White	1/7/2008	NaN	N/A-StillEmployed	Active	Production	Elijiah Gray	16.0	Indeed	Fully Meets	4.84	5	0	1/3/2019	15
4	Anderson, Carol	10069	0	2	0	5	5	3	0	50825	1	19	Production Technician I	MA	2169	09/08/89	F	Divorced	US Citizen	No	White	7/11/2011	9/6/2016	return to school	Voluntarily Terminated	Production	Webster Butler	39.0	Google Search	Fully Meets	5.00	4	0	2/1/2016	2
5	Anderson, Linda	10002	0	0	0	1	5	4	0	57568	0	19	Production Technician I	MA	1844	05/22/77	F	Single	US Citizen	No	White	1/9/2012	NaN	N/A-StillEmployed	Active	Production	Amy Dunn	11.0	LinkedIn	Exceeds	5.00	5	0	1/7/2019	15
6	Andreola, Colby	10194	0	0	0	1	4	3	0	95660	0	24	Software Engineer	MA	2110	05/24/79	F	Single	US Citizen	No	White	11/10/2014	NaN	N/A-StillEmployed	Active	Software Engineering	Alex Sweetwater	10.0	LinkedIn	Fully Meets	3.04	3	4	1/2/2019	19
7	Athwal, Sam	10062	0	4	1	1	5	3	0	59365	0	19	Production Technician I	MA	2199	02/18/83	M	Widowed	US Citizen	No	White	9/30/2013	NaN	N/A-StillEmployed	Active	Production	Ketsia Liebig	19.0	Employee Referral	Fully Meets	5.00	4	0	2/25/2019	19
8	Bachiochi, Linda	10114	0	0	0	3	5	3	1	47837	0	19	Production Technician I	MA	1902	02/11/70	F	Single	US Citizen	No	Black or African American	7/6/2009	NaN	N/A-StillEmployed	Active	Production	Brannon Miller	12.0	Diversity Job Fair	Fully Meets	4.46	3	0	1/25/2019	4
9	Bacong, Alejandro	10250	0	2	1	1	3	3	0	50178	0	14	IT Support	MA	1886	01/07/88	M	Divorced	US Citizen	No	White	1/5/2015	NaN	N/A-StillEmployed	Active	IT/IS	Peter Monroe	7.0	Indeed	Fully Meets	5.00	5	6	2/18/2019	16

	Employee_Name	EmpID	MarriedID	MaritalStatusID	GenderID	EmpStatusID	DeptID	PerfScoreID	FromDiversityJobFairID	Salary	Termd	PositionID	Position	State	Zip	DOB	Sex	MaritalDesc	CitizenDesc	HispanicLatino	RaceDesc	DateofHire	DateofTermination	TermReason	EmploymentStatus	Department	ManagerName	ManagerID	RecruitmentSource	PerformanceScore	EngagementSurvey	EmpSatisfaction	SpecialProjectsCount	LastPerformanceReview_Date	DaysLateLast30	Absences
301	Wilber, Barry	10048	1	1	1	5	5	3	0	55140	1	19	Production Technician I	MA	2324	09/09/65	M	Married	Eligible NonCitizen	No	White	5/16/2011	9/7/2015	unhappy	Voluntarily Terminated	Production	Amy Dunn	11.0	Website	Fully Meets	5.00	3	0	2/15/2015	0	7
302	Wilkes, Annie	10204	0	2	0	5	5	3	0	58062	1	19	Production Technician I	MA	1876	07/30/83	F	Divorced	US Citizen	No	White	1/10/2011	5/14/2012	Another position	Voluntarily Terminated	Production	Ketsia Liebig	19.0	Google Search	Fully Meets	3.60	5	0	2/6/2011	0	9
303	Williams, Jacquelyn	10264	0	0	0	5	5	3	1	59728	1	19	Production Technician I	MA	2109	10/02/69	F	Single	US Citizen	Yes	Black or African American	1/9/2012	6/27/2015	relocation out of area	Voluntarily Terminated	Production	Ketsia Liebig	19.0	Diversity Job Fair	Fully Meets	4.30	4	0	6/2/2014	0	16
304	Winthrop, Jordan	10033	0	0	1	5	5	4	0	70507	1	20	Production Technician II	MA	2045	11/07/58	M	Single	US Citizen	No	White	1/7/2013	2/21/2016	retiring	Voluntarily Terminated	Production	Brannon Miller	12.0	LinkedIn	Exceeds	5.00	3	0	1/19/2016	0	7
305	Wolk, Hang T	10174	0	0	0	1	5	3	0	60446	0	20	Production Technician II	MA	2302	04/20/85	F	Single	US Citizen	No	White	9/29/2014	NaN	N/A-StillEmployed	Active	Production	David Stanley	14.0	LinkedIn	Fully Meets	3.40	4	0	2/21/2019	0	14
306	Woodson, Jason	10135	0	0	1	1	5	3	0	65893	0	20	Production Technician II	MA	1810	05/11/85	M	Single	US Citizen	No	White	7/7/2014	NaN	N/A-StillEmployed	Active	Production	Kissy Sullivan	20.0	LinkedIn	Fully Meets	4.07	4	0	2/28/2019	0	13
307	Ybarra, Catherine	10301	0	0	0	5	5	1	0	48513	1	19	Production Technician I	MA	2458	05/04/82	F	Single	US Citizen	No	Asian	9/2/2008	9/29/2015	Another position	Voluntarily Terminated	Production	Brannon Miller	12.0	Google Search	PIP	3.20	2	0	9/2/2015	5	4
308	Zamora, Jennifer	10010	0	0	0	1	3	4	0	220450	0	6	CIO	MA	2067	08/30/79	F	Single	US Citizen	No	White	4/10/2010	NaN	N/A-StillEmployed	Active	IT/IS	Janet King	2.0	Employee Referral	Exceeds	4.60	5	6	2/21/2019	0	16
309	Zhou, Julia	10043	0	0	0	1	3	3	0	89292	0	9	Data Analyst	MA	2148	02/24/79	F	Single	US Citizen	No	White	3/30/2015	NaN	N/A-StillEmployed	Active	IT/IS	Simon Roup	4.0	Employee Referral	Fully Meets	5.00	3	5	2/1/2019	0	11
310	Zima, Colleen	10271	0	4	0	1	5	3	0	45046	0	19	Production Technician I	MA	1730	08/17/78	F	Widowed	US Citizen	No	Asian	9/29/2014	NaN	N/A-StillEmployed	Active	Production	David Stanley	14.0	LinkedIn	Fully Meets	4.50	5	0	1/30/2019	0	2

Overview

Variables

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Other Punctuation

Space Separator

Dash Punctuation

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script